Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

NeuRoute: Predictive Dynamic Routing for Software-Defined Networks

This paper introduces NeuRoute, a dynamic routing framework for Software Defined Networks (SDN) entirely based on machine learning, specifically, Neural Networks. Current SDN/OpenFlow controllers use a default routing based on Dijkstra algorithm for shortest paths, and provide APIs to develop custom routing applications. NeuRoute is a controller-agnostic dynamic routing framework that (i) predicts traffic matrix in real time, (ii) uses a neural network to learn traffic characteristics and (iii) generates forwarding rules accordingly to optimize the network throughput. NeuRoute achieves the same results as the most efficient dynamic routing heuristic but in much less execution time.Comment: Accepted for CNSM 201

Review of Path Selection Algorithms with Link Quality and Critical Switch Aware for Heterogeneous Traffic in SDN

Software Defined Networking (SDN) introduced network management flexibility that eludes traditional network architecture. Nevertheless, the pervasive demand for various cloud computing services with different levels of Quality of Service requirements in our contemporary world made network service provisioning challenging. One of these challenges is path selection (PS) for routing heterogeneous traffic with end-to-end quality of service support specific to each traffic class. The challenge had gotten the research community\u27s attention to the extent that many PSAs were proposed. However, a gap still exists that calls for further study. This paper reviews the existing PSA and the Baseline Shortest Path Algorithms (BSPA) upon which many relevant PSA(s) are built to help identify these gaps. The paper categorizes the PSAs into four, based on their path selection criteria, (1) PSAs that use static or dynamic link quality to guide PSD, (2) PSAs that consider the criticality of switch in terms of an update operation, FlowTable limitation or port capacity to guide PSD, (3) PSAs that consider flow variabilities to guide PSD and (4) The PSAs that use ML optimization in their PSD. We then reviewed and compared the techniques\u27 design in each category against the identified SDN PSA design objectives, solution approach, BSPA, and validation approaches. Finally, the paper recommends directions for further research

Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks

لضمان الإستجابة للخطأ والإدارة الموزعة، يتم استخدام البروتوكولات الموزعة كأحد المفاهيم المعمارية الرئيسية التي تتضمنها شبكة الإنترنت. ومع ذلك، يمكن التغلب على عدم الكفاءة وعدم الاستقرار والقصور بمساعدة بنية الشبكات الجديدة التي تسمى الشبكات المعرفة بالبرمجيات SDN. الخاصية الرئيسية لهذه المعمارية هي فصل مستوى التحكم عن مستوى البيانات. إن تقليل التصادم سيؤدي إلى تحسين سرعة الإستجابة وزيادة البيانات المرسلة بصورة صحيحة، لهذا السبب يجب أن يكون هناك توزيع متجانس للحمل المروري عبر مسارات الشبكة المختلفة. تقدم هذه الورقة البحثية أداة توجيه ذكية SFSA لتوجيه تدفق البيانات بناءاً على ظروف الشبكة الحالية. لتحسين الإنتاجية وتقليل زمن الوصول، فإن الخوارزمية المقترحة SFSA تقوم بتوزيع حركة مرور البيانات داخل الشبكة على مسارات مناسبة ، بالإضافة إلى الإشراف على الإرتباطات التشعبية وحمل مسارات نقل البيانات. تم استخدام سيناريو خوارزمية توجيه شجرة الامتداد الدنياMST وأخرى مع خوارزمية التوجيه المعروفة بفتح أقصر مسار أولاً OSPF لتقييم جودة الخوارمية المقترحة SFSA . على سبيل المقارنة ، بالنسبة لخوارزميات التوجيه المذكروة آنفاً ، فقد حققت استراتيجيةSFSA المقترحة انخفاضاً بنسبة 2٪ في معدل ضياع حزم البيانات PDR ، وبنسبة تتراوح بين 15-45٪ في سرعة إستلام البيانات من المصدر إلى الالوجهة النهائية لحزمة البيانات وكذلك انخفاض بنسبة 23 ٪ في زمن رحلة ذهاب وعودة RTT . تم استخدام محاكي Mininet ووحدة التحكم POX لإجراء المحاكاة. ميزة أخرى من SFSA على MST و OSPF هي أن وقت التنفيذ والاسترداد لا يحمل تقلبات. يتقوم أداة التوجيه الذكية المقترحة في هذه الورقة البحثية من فتح أفقاً جديداً لنشر أدوات ذكية جديدة في شبكة SDN تعزز قابلية برمجة الشبكات وإدارتها .To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management

The CASPER user-centric approach for advanced service provisioning in mobile networks

Abstract This paper presents an overview of the project CASPER, 1 a 4-year Marie Curie Research and Innovation Staff Exchange (RISE) project running between 2016 and 2020, describing its objectives, approach, architecture, tools and key achievements. CASPER combines academic and industrial forces towards leveraging the expected benefits of Quality of Experience (QoE) exploitation in future networks. In order to achieve that, a QoE orchestrator has been proposed which implements the basic functionalities of QoE monitoring, estimation and management. With means of simulation and testbed emulation, CASPER has managed to develop a proprietary SDN Controller, which implements QoE-based traffic rerouting for the challenging scenario of HTTP adaptive video streaming, leading to more stable and higher QoE scores compared to a state-of-the-art SDN Controller implementation